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This is a Cohort Study study (also classified as: Quantitative Study).

October 15, 2025

Assessing Sarcasm Dataset Quality

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Analysis demonstrates sarcasm detection improvements in sentiment analysis using refined datasets, indicating data quality's importance.

The NewsHeadline dataset achieved the highest F1-score of 0.93, indicating its superior quality for sarcasm detection.
Models utilized for dataset evaluation included statistical machine learning, deep learning, and transfer learning approaches.
To combat class imbalance, two resampling techniques—oversampling and undersampling—were applied during model training.
A refined Sarcasm-Quality dataset was released to support future research in sarcasm-aware natural language processing systems.

Bade et al. (2025) studied this question.

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